MST-Department of Statistics and Actuarial Science

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Browsing MST-Department of Statistics and Actuarial Science by Subject "South Imenti Sub County"

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    A Statistical Application of Regression Analysis to Investigate and Determine the Factors That Influence the Uptake of Family Planning in South Imenti Sub County - Meru County
    (kenyatta university, 2023) Mpuria, Thomas Bundi; James Kahiri
    Family planning is one of the mitigation factors adopted by the Kenyan Government in achieving its strategic development goals through reducing child mortality and maternal mortality, thwarting unwanted pregnancies, prevention of STDs, promoting education and the economic empowerment of women. Despite many advantages of family planning, its utilization and adoption in Kenya is still low. Unwanted pregnancies, premature deliveries, illegal abortions and maternal mortality have all resulted from a low uptake of family planning. The low application of family planning methods has been associated with low awareness of existence of family planning methods, lack of information about various forms of family planning methods, negative attitude toward some family planning methods due to lack of counselling/sensitization to mothers on their side effects, difficulty in assessing the family planning services by some rural women, religious beliefs and fear of not being able to bear children again. South Imenti is a Sub County in Meru County associated with low uptake of family planning services despite being offered free of charge in all government clinics. Statistics from the recent census done in the year 2019 indicate that there are more young girls aged between 15-24 years with children, which indicates that teenage pregnancies are rampant. This implies that the uptake of family planning resources is still very low despite numerous sensitization programs. The goal of this study was to apply binary logistic regression method to examine factors that impact on the usage of family planning methods in South Imenti sub-county. The target population was 9,900 women between the ages of 15 and 49. A total of 385 mothers were chosen using stratified simple random sampling for this survey. The study used descriptive and binary logistic regression methods of analysis. The explanatory variables included education level, age, marital status number of children born, Religion, Occupation, household income and frequency of listening to media. In conclusion, the application of binary logistic regression model on the data collected showed that age, education level, marital status, number of children and frequency of mothers in following media were potential explanatory variables that have a significant effect on the utilization of family planning practices.